CN109685877A - A kind of micro-nano CT focus drifting bearing calibration based on adaptive projected image Character Area Matching - Google Patents
A kind of micro-nano CT focus drifting bearing calibration based on adaptive projected image Character Area Matching Download PDFInfo
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Abstract
The micro-nano CT focus drifting bearing calibration based on adaptive projected image Character Area Matching that the present invention relates to a kind of, belongs to CT technical field of imaging.This method comprises: S1: scanning testee obtains one group of actual projection images；S2: in the case where not stopping beam, keeping other sweep parameters constant, carries out primary a small amount of visual angle, the CT scan of short time immediately, obtains one group of reference projection images；S3: actual projection images and reference projection images under relatively more corresponding visual angle obtain the focus drifting amount under corresponding visual angle by self-adaptive features Region Matching；S4: the focus drifting amount under remaining visual angle is calculated using cubic spline interpolation, obtains the drift value of actual projection data under all visual angles；S5: amendment actual projection images, and image reconstruction is carried out, obtain testee clearly CT 3-D image.The present invention can accurately and fast correct focus drifting amount, not only saved detection time but also reduced equipment loss.
Description
Technical field
The invention belongs to CT technical field of imaging, are related to a kind of micro-nano CT focus based on projected image Character Area Matching
Drift correction method.
Background technique
Computed tomography (Computed Tomography, CT) is used as a kind of advanced non-destructive testing technology,
Have many advantages, such as not damaged, high resolution, is widely used to industry and medical domain.In recent years, with radiographic source and detection
The promotion of device technical level, high-resolution cone-beam micro-nano CT are rapidly developed.In CT imaging process, increase sampling is generallyd use
Time and the average mode of frame improve signal-to-noise ratio, and the lengthening of sweep time also imply that the system of increasing unstability and
Inaccuracy.Studies have shown that the energy for only having 1% in X-ray tube is converted into X-ray, remaining 99% energy is all converted to heat
Energy.Therefore, x-ray focus position can drift about because of the stability of electron beam and the thermal change type of ray tube, so as to cause
There is deviation in the received projected position of detector, eventually leads to image definition and is remarkably decreased.The ray source focus of common CT is big
Small is 0.4-2mm, and micro-nano CT ray source focus size reaches micron order even submicron order, and the small drift of focus all can be right
Picture quality produces a very large impact.Focus drifting is divided into static drift and dynamic drift, and static drift refers to open source transient deflections,
And dynamic drift is then applied in the entire scanning process of CT, correction difficulty is big, and the present invention conducts a research around dynamic drift.
Current focus drifting bearing calibration can mainly be attributed to following a few classes: first method needs to utilize straightening die
Type solves focus drifting amount by tracking the variation of primary standard substance as the primary standard substance in projected image.Gullberg and
Bronikov is respectively in the typical case that the technology based on object and open mould that nineteen ninety and 1999 propose is such method
It represents；Second method is to correct focus drifting using acquisition auxiliary data, belongs to software correction method, is compensated with reference to projection
One kind owned by France in this method；The third method had not both needed not needing additional scanning in measured zone setting flag object yet
Projection is directly iterated correction using projected image, and this method is time-consuming and calibration result is undesirable.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of micro-nano CT focus based on projected image Character Area Matching
Drift correction method is used for overcome the deficiencies in the prior art, obtains focus drift using the reference projection matching mode quickly scanned
Shifting amount uses iteration self-adapting Character Area Matching method solving focus drifting process, can accurately and fast correct focus drift
It moves, this method is easy to operate, real-time is good, had not only saved detection time but also had reduced equipment loss.
In order to achieve the above objectives, the invention provides the following technical scheme:
A kind of micro-nano CT focus drifting bearing calibration based on adaptive projected image Character Area Matching, specifically include with
Lower step:
S1: testee is scanned using micro-nano CT system, obtains one group of actual projection images；
S2: in the case where not stopping beam, keeping other sweep parameters constant, carries out primary a small amount of visual angle, short time immediately
CT scan, obtain one group of reference projection images；
S3: actual projection images and reference projection images under relatively more corresponding visual angle, and pass through self-adaptive features region
Match, obtains the focus drifting amount under corresponding visual angle；
S4: the focus drifting amount under remaining visual angle is calculated using cubic spline interpolation, obtains and is actually projected under all visual angles
The drift value of data；
S5: actual projection images are corrected using obtained focus drifting amount, and carry out image reconstruction, to finally obtain
Testee clearly CT 3-D image.
Further, the practical projection in the step S1 and S2 and reference projection are the projected images under corresponding visual angle, real
When property and matching are good；
Further, in the step S2, carry out reference scan is still testee, does not need other model-aideds,
And radiographic source is after scanning a period of time, then when carrying out the short time and quickly scanning, focus be it is stable, reference scan is as ideal
Data for projection.Experimental study show radiographic source beam out about after twenty minutes, focal position substantially stablize it is constant.
Further, the practical projection view angles number in the step S1 is the integral multiple that projection view angles number is referred in S2 step,
Multiple usually takes 10, with guarantee reference scan more rapidly, real-time it is more preferable；
Further, the specific steps that focus drifting amount is solved by self-adaptive features Region Matching in the step S3
Are as follows:
S31: segmentation testee projected image, including actual projection images and reference projection images；
S32: the characteristic area of tested projection is extracted, and seeks the mass center of characteristic area；
S33: the offset projected under corresponding visual angle is solved, and focus drifting amount is solved according to amplification factor.
Further, in the step S31, divide testee before, using gray scale normalization method first to projected image into
Row enhancing, i.e., be normalized to the double-precision floating points between [0,1] for input data, normalizes formula are as follows:
I (x, y)=(I (x, y)-Imin))/(Imax-Imin)
Wherein, ImaxFor the maximum gradation value of image I, IminFor the minimum gradation value of image I.
Further, in the step S31, segmentation testee uses the adaptive threshold fuzziness based on iterative method；Part
The selection focus point offset accuracy influence of segmentation of feature regions threshold value is very big, if threshold value chooses improper, the figure divided
As blur margin is clear or discrete point is more, it is big to will lead to the mass center deviation sought, and it is big to eventually lead to focus deviation error.Using
Iterative method adaptively obtains segmentation threshold, is suitable for various projected images.The iterative method essence is the think of approached based on optimization
Think.Specifically:
1) an initial threshold value T is selected0If the maximum gradation value and minimum gradation value of image are respectively ImaxAnd Imin,
Then T0=(Imax+Imin)/2；
2) according to threshold value T0Foreground and background is divided the image into, and finds out two-part average gray IaAnd Ib, according to IaWith
IbSelect new threshold value T=(Ia+Ib)/2；
3) step 2) is repeated, until T no longer changes to arrive final threshold value T.
Further, in the step S32, the extracting method of the characteristic area is search whole image, obtains image
Some characteristic point coordinate, it is as a reference point, the same section of correspondence image is intercepted with this.Due to perspective view not necessarily cover by
All profiles for surveying object, in the case where projection is drifted about, are detected object projected area if seeking the mass center entirely projected
The size in domain can change, and mass center cannot be as the characteristic point for solving focus drifting, therefore only extracts characteristic area
Just it is able to achieve the accurate matching of projected image.
Further, in the step S32, it is as follows that the mass center of the tested projected image characteristic area seeks formula:
Wherein,The as center-of-mass coordinate of projected image characteristic area, μ (x, y) are the gray value of pixel (x, y),
D indicates that the local characteristic region of projected image, M indicate the sum of characteristic area all pixels gray scale.By the reality under corresponding visual angle
The center-of-mass coordinate of projection and reference projection is matched, and the project migration amount under the visual angle is obtained, then according to the amplification of system
Multiple can find out the focus drifting amount under the visual angle.
Further, the cubic spline interpolation in the step S4 is that one kind obtains accurate coke in the case where projecting the smaller situation of sample
The optimal interpolation method of point drift amount.
Further, it in the step S5, is asked in the way of actual projection images and reference projection images Character Area Matching
Focus drifting amount is obtained to correct actual projection images, and carries out image reconstruction, to obtain testee clearly CT three-dimensional figure
Picture.
The beneficial effects of the present invention are: bearing calibration of the present invention does not need calibration model, easy to operate, real-time
It is good, it had not only saved the time but also had reduced equipment loss；The focus drifting amount that self-adaptive features Region Matching method solves is more accurate, and phase
Faster than the method for registering speed based on frequency domain and gray scale.The experimental results showed that the focus drifting positioning of this method is quickly, accurately,
Picture quality can be significantly improved.
Detailed description of the invention
In order to keep the purpose of the present invention, technical scheme and beneficial effects clearer, the present invention provides following attached drawing and carries out
Illustrate:
Fig. 1 is micro-nano CT focus drifting bearing calibration implementation flow chart of the present invention；
Fig. 2 is the focus drifting amount of bamboo fibre with the change curve of sweep time；
Fig. 3 is laterally consecutive three layers of slice after uncorrected backprojection reconstruction；
Fig. 4 is slices across of the image after focus drifting corrects in Fig. 3；
Fig. 5 be uncorrected backprojection reconstruction after be longitudinally continuous three layers of slice；
Fig. 6 is longitudinal section of the image after focus drifting corrects in Fig. 5.
Specific embodiment
Below in conjunction with attached drawing, a preferred embodiment of the present invention will be described in detail.
Equipment used in the present invention is unless otherwise required common device in the art；The present invention
Used in method be unless otherwise required common method in the art.
As shown in Figure 1, a kind of micro-nano CT focus drifting school based on projected image Character Area Matching of the present invention
Correction method, step include:
S1: testee is scanned using micro-nano CT system, obtains one group of practical CT data for projection；
S2: in the case where not stopping beam, keeping other sweep parameters constant, carries out primary a small amount of visual angle, short time immediately
CT scan, obtain one group refer to data for projection；
S3: actual projection images and reference projection images under relatively more corresponding visual angle, and pass through self-adaptive features region
Match, obtains the focus drifting amount under corresponding visual angle；
S4: calculating the focus drifting amount under remaining visual angle using cubic spline interpolation, thus to obtain practical under all visual angles
The drift value of data for projection；
S5: actual projection images are corrected using obtained focus drifting amount, and carry out image reconstruction, are finally tested
Object clearly CT 3-D image.
Carry out reference scan in the S2 is still testee, does not need other model-aideds.When radiographic source scans
After a period of time, then when carrying out the short time and quickly scanning, focus is stable, therefore reference scan can be used as ideal projection number
According to.
Practical projection and reference projection in the S1 and S2 are the projected image under corresponding visual angle, real-time and matching
It is good；
Self-adaptive features Region Matching method in the S3 solves focus drifting amount, and specific step is as follows:
(1) divide testee projected image, including actual projection images and reference projection images；
(2) characteristic area of tested projection is extracted, and seeks the mass center of characteristic area；
(3) offset projected under corresponding visual angle is solved, and focus drifting amount is solved according to the amplification factor of system.
Before dividing testee in the S3, first projected image is enhanced, the present invention's is gray scale normalization
Method, i.e., the double-precision floating points being normalized to input data between [0,1].Normalizing formula is
I (x, y)=(I (x, y)-Imin))/(Imax-Imin)
Wherein, ImaxFor the big value of most gray scale of image I, IminFor the minimum gradation value of image I.
Using the adaptive threshold fuzziness based on iteration in the S3.The selection pair of local characteristic region segmentation threshold
The influence of focus deviation accuracy is very big, if threshold value selection is improper, the image border divided is unintelligible or discrete point is more,
It is big to will lead to the mass center deviation sought, it is big to eventually lead to focus deviation error.Iterative method of the present invention can be adaptive
Segmentation threshold should be obtained, various projected images are suitable for.The iterative method essence is the thought approached based on optimization.Implementation method
It is as follows:
(1) an initial threshold value T is selected0.If the maximum gradation value and minimum gradation value of image are respectively ImaxAnd Imin,
Then T0=(Imax+Imin)/2；
(2) foreground and background is divided the image into according to threshold value T0, and finds out two-part average gray IaAnd Ib, according to Ia
And IbSelect new threshold value T=(Ia+Ib)/2；
(3) (2) step is repeated, until T no longer changes to arrive final threshold value T.
The method that characteristic area is extracted in the S3 is search whole image, obtains some characteristic point coordinate of image, is made
For reference point, the same section of correspondence image is intercepted with this.Due to not necessarily covering all wheels of testee in perspective view
Exterior feature, if seeking the mass center entirely projected, in the case where focus is drifted about, the projected position and size of object can become
Change, mass center cannot be as the characteristic point for solving focus drifting, it is therefore necessary to extract characteristic area.
It is as follows to seek formula for the mass center of characteristic area in the S3:
Wherein,The as center-of-mass coordinate of projected image characteristic area, μ (x, y) are the gray value of pixel (x, y),
D indicates that the local characteristic region of projected image, M indicate the sum of characteristic area all pixels gray scale.By the reality under corresponding visual angle
The center-of-mass coordinate of projection and reference projection is matched, and is obtained the offset projected under the visual angle, is found out further according to amplification factor
Focus drifting amount.
Cubic spline interpolation in the step S4 is under a kind of less projection view angles, obtains compared with exact focus drift value
Optimal interpolation method, algorithm are as follows:
Assuming that there is n+1 node (a0,b0),(a1,b1),...,(ai,bi),...,(an,bn),
(1) material calculation hi=ai+1-ai(i=0,1.2......n+1)；
(2) above-mentioned node and head and the tail end-point condition are substituted into matrix equation；
(3) dematrix equation acquires second differential value pi.The matrix is triple diagonal matrix；
(4) coefficient of cubic spline interpolation is solved:
mi=bi
(5) it can be obtained by interpolation equation between every two node:
fi(a)=mi+ni(a-ai)+ki(a-ai)2+li(a-ai)3
In the present embodiment, the implementation of the method for the present invention is illustrated so that the CT scan data to bamboo fibre is rebuild as an example
Journey.
A kind of micro-nano CT focus drifting bearing calibration based on projected image Character Area Matching, step include:
S1: testee is scanned using micro-nano CT system, obtains one group of practical CT data for projection；In experiment to bamboo fibre into
The actual scanning at 1000 visual angles of row.Fig. 3 is laterally consecutive three layers of slice after uncorrected practical backprojection reconstruction, and Fig. 5 is not
Correction is longitudinally continuous three layers of slice；
S2: in the case where not stopping beam, primary a small amount of visual angle, the CT scan of short time are carried out immediately, obtains one group 100
The reference data for projection at visual angle；
S3: actual projection images and reference projection images under relatively more corresponding visual angle, and pass through self-adaptive features region
The focus drifting amount under the visual angle is obtained with method；
S4: the focus drifting amount under other visual angles is calculated using cubic spline interpolation, obtains the drift of all data for projection
Amount, as shown in Figure 2；
S5: correcting actual projection images using obtained focus drifting amount, and carry out image reconstruction using FDK algorithm,
The final 3-D image for obtaining testee.Fig. 4 is the effect picture after slices across corresponding with Fig. 3 correction, and Fig. 6 is and Fig. 5 pairs
Effect picture after answering longitudinal section to correct.
Select bamboo fibre for experiment sample in embodiment, sweep parameter is as shown in table 1, and environment temperature is 25 DEG C, and humidity is
79%.It can be seen that, focus drifting causes image integrally relatively fuzzyyer, and internal structure is complete from the uncorrected slice of Fig. 2 and Fig. 4
It cannot differentiate entirely, and after correcting by means of the present invention, as shown in figs. 3 and 5, the clarity of image significantly improves, image mould
Paste and distortion significantly reduce, and picture quality is significantly improved.
The sweep parameter table of 1 actual experiment of table
Finally, it is stated that preferred embodiment above is only used to illustrate the technical scheme of the present invention and not to limit it, although logical
It crosses above preferred embodiment the present invention is described in detail, however, those skilled in the art should understand that, can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (8)
1. a kind of micro-nano CT focus drifting bearing calibration based on adaptive projected image Character Area Matching, which is characterized in that
The bearing calibration specifically includes the following steps:
S1: testee is scanned using micro-nano CT system, obtains one group of actual projection images；
S2: in the case where not stopping beam, keeping other sweep parameters constant, carries out primary a small amount of visual angle, the CT of short time immediately
Scanning obtains one group of reference projection images；
S3: actual projection images and reference projection images under relatively more corresponding visual angle, and by self-adaptive features Region Matching, it obtains
Obtain the focus drifting amount under corresponding visual angle；
S4: the focus drifting amount under remaining visual angle is calculated using cubic spline interpolation, obtains actual projection data under all visual angles
Drift value；
S5: actual projection images are corrected using obtained focus drifting amount, and carry out image reconstruction, to be finally tested
Object clearly CT 3-D image.
2. micro-nano CT focus drifting bearing calibration according to claim 1, which is characterized in that in the step S2, carry out
Reference scan is still testee, does not need other model-aideds, and radiographic source is after scanning a period of time, then is carried out short
When time is quickly scanned, focus be it is stable, reference scan is as ideal data for projection.
3. micro-nano CT focus drifting bearing calibration according to claim 1, which is characterized in that passing through in the step S3
Self-adaptive features Region Matching solves the specific steps of focus drifting amount are as follows:
S31: segmentation testee projected image, including actual projection images and reference projection images；
S32: tested projected image characteristic area is extracted, and seeks the mass center of characteristic area；
S33: the offset projected under corresponding visual angle is solved, and focus drifting amount is solved according to amplification factor.
4. micro-nano CT focus drifting bearing calibration according to claim 3, which is characterized in that in the step S31, segmentation
Before testee, first projected image is enhanced using gray scale normalization method, i.e., by input data be normalized to [0,1] it
Between double-precision floating points, normalize formula are as follows:
I (x, y)=(I (x, y)-Imin))/(Imax-Imin)
Wherein, ImaxFor the maximum gradation value of image I, IminFor the minimum gradation value of image I.
5. micro-nano CT focus drifting bearing calibration according to claim 3, which is characterized in that in the step S31, use
Iterative method adaptively obtains segmentation threshold, the iterative method specifically:
1) an initial threshold value T is selected0If the maximum gradation value and minimum gradation value of image are respectively ImaxAnd Imin, then T0=
(Imax+Imin)/2；
2) according to threshold value T0Foreground and background is divided the image into, and finds out two-part average gray IaAnd Ib, according to IaAnd IbChoosing
Select new threshold value T=(Ia+Ib)/2；
3) step 2) is repeated, until T no longer changes to arrive final threshold value T.
6. micro-nano CT focus drifting bearing calibration according to claim 3, which is characterized in that described in the step S32
The extracting method of characteristic area is search whole image, obtains some characteristic point coordinate of image, as a reference point, is intercepted with this
The same section of correspondence image.
7. micro-nano CT focus drifting bearing calibration according to claim 3, which is characterized in that described in the step S32
The mass center of tested projected image characteristic area seeks formula are as follows:
Wherein,The as center-of-mass coordinate of projected image characteristic area, μ (x, y) are the gray value of pixel (x, y), and D is indicated
The local characteristic region of projected image, M indicate the sum of characteristic area all pixels gray scale.
8. micro-nano CT focus drifting bearing calibration according to claim 1, which is characterized in that in the step S5, utilize
Actual projection images and reference projection images Character Area Matching mode acquire focus drifting amount to correct actual projection images, and
Image reconstruction is carried out, to obtain testee clearly CT 3-D image.
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| CN112461872B (en) * | 2020-10-16 | 2023-01-24 | 天津大学 | micro-CT focal spot drift measurement system based on double-microsphere mold body and compensation method |
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